Triple
T16105522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Perfect World |
E390727
|
entity |
| Predicate | manhuntTheme |
P121956
|
FINISHED |
| Object | fugitive pursued by Texas law enforcement |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: fugitive pursued by Texas law enforcement | Statement: [A Perfect World, manhuntTheme, fugitive pursued by Texas law enforcement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: manhuntTheme Context triple: [A Perfect World, manhuntTheme, fugitive pursued by Texas law enforcement]
-
A.
The Grave_theme
Indicates a relationship where an entity serves as the thematic or symbolic focus associated with a grave or burial context.
-
B.
gameOfDeath
Indicates a relationship where an entity is involved in, associated with, or characterized by a lethal contest, challenge, or deadly event.
-
C.
comicTheme
Indicates that something (such as a work, scene, or element) centers around or is characterized by a humorous or comic theme.
-
D.
murderedIn
Indicates that one entity unlawfully killed another entity at or within a specified location.
-
E.
gameTheme
Indicates the central subject, style, or conceptual focus that characterizes a game.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6b91a48190a04648d4cad2c4b1 |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e182804208819087f35307cd6e4103 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 5 a.m.